Using an algorithm to be an upstander in the face of discrimination

The events of the past year are a powerful reminder of the prevalence of racism and discrimination that non-white Americans face on a daily basis. The recent statement from the Centers for Disease Control and Prevention that racism is a public health issue reinforces the need for the medical community to address the issues with patients, but what happens when the person experiencing the racism or discrimination is a colleague and whoever does the discrimination is a patient or a family member? At the virtual meeting of Pediatric Academic Societies in 2021, Sahar Rahiem, MD, MHS, a resident of Texas Children’s Hospital and Baylor College of Medicine in Houston, discussed a model she had created with colleagues to turn someone from a bystander into a rebel to change.

Rahiem and her colleagues began their research because discrimination by family or patients is common, accounting for 22% of the discrimination trainees face, but is puzzling. Doctors want to have a good rapport with the patients because that improves care outcomes and the likelihood of adherence, but colleagues need support and a lack of response can be seen as not giving the discrimination or even agreeing with the discrimination .

The model created by the team was taught in a workshop and involved 3 steps:

determine the stage at which the clinicians were told what would happen by working out a set scenario that fits one of three possible types of discrimination, (1) discriminatory statement, for example, “I’m so glad you’re a white doctor “(2) a discriminatory request, eg,” Can we please have a white doctor “, or (3) mistaken identity, eg, a patient or family member acting like a black doctor, is on the janitor’s staff. during the role-playing session. Each type of discrimination had an algorithm to respond.

Rahiem presented how the algorithm would work with a discriminatory statement. The first step is to assess the child’s medical condition. If the condition is unstable, clinicians should provide urgent medical treatment and conduct a debriefing session later. If the child is stable, the doctor should determine how to respond based on whether the claim was overly discriminatory or a microaggression. In the case of overt discrimination, a physician should use “I” statements and make the position clear with a statement such as “I ask you not to use that language while your child is being treated by our medical staff. In cases of micro-aggressions, the doctor should present the statement with an ‘I’ statement, such as ‘What I have heard is that you think …’. In either case, the doctor must refer the conversation back to the child’s medical care. After a meeting, a clinician should tell other colleagues what happened and a debrief should take place.

According to Rahiem, the study participants found it very helpful and many indicated that the lessons learned in the workshop would lead to changes in clinical practice. Many of the participants also said that the algorithms used were helpful, and many indicated that they felt better equipped to handle situations in the future because of the

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